Frontline worker from the Cali Public Health Secretary during a usability testing session. Photo by: Premise

The recent Zika outbreak has put Latin American cities at the forefront of the battle against infectious diseases. Mosquitoes are the deadliest animals on the planet, causing more than 1 million deaths each year. Yet mosquito-borne diseases are preventable. To control the disease risks, health authorities use a combination of techniques, including abating breeding sites and fumigating residential areas.

But most city governments struggle to deliver efficient prevention and remediation. Relying on highly manual operations, they are forced to canvass large-scale urban areas in search of standing water containers, which continuously spring up after rain showers. It is a needle-in-a-haystack problem that puts a strain on municipal resources and fails to effectively protect citizens from emerging health threats.

Now, mobile and cloud-based technology can guide health workers in the field and provide real-time risk assessment to power more targeted remediation efforts. By unlocking environmental risk data, new technologies help cities act smarter about where to look for mosquitoes and how to fight them. But to be truly transformative, tech products need to be designed to work in resource-constrained local conditions; they need to be highly adaptive, context-sensitive and user-centric.

Next-generation risk management tech: Cali’s pilot project

Premise has developed an integrated technology platform that enhances the speed and effectiveness of vector surveillance, targets control efforts and activates citizen networks for reporting and remediation.

With the support of the U.S. Agency for International Development, Premise and the Colombian city of Cali are piloting the implementation of the next generation of smart vector management technology. A city of 2.3 million people, which is also hyperendemic for dengue, Cali accounted for 23 percent of Colombia’s Zika cases in 2016, the world’s second-largest Zika outbreak, after Brazil’s.

Hyper adaptability to context

To enable the delivery of core public services more efficiently, technology must thrive in local infrastructure and operating conditions. In the Colombian city of Cali, for example, people often leave newer phones at home, and take cheaper ones out on daily duties. In this context, app performance on low-cost phones is critical. Low battery and memory usage, as well as offline or asynchronous mobile-based data collection are also key to support full-day operations in the field. At Premise, we have set up networks that replicate connectivity conditions in rural parts of Africa to test app performance in real-world conditions.

Implementing new technology for resilient cities requires configuring standardized platforms to local operations and needs. It involves digging into the minutiae of operational programs, and understanding organizational patterns for triggering interventions, assigning work and consuming data outputs. This enables pulling on the right operational strings to deploy optimization strategies — improving treatment coverage through workers’ dynamic goal setting or ensuring aedes detection is correctly performed through personalized training.

New technology tools need to provide the flexibility to integrate decades-old programs with unwritten rules, while setting the foundations for improvement. For example, Cali’s flagship surveillance program monitors 54,000 storm drain access points several times a month. While roughly known by workers, these locations are not uniquely identifiable, and they are grouped into non-standardized areas for functional ease. Incorporating heuristic standards while geo-tagging activities on the platform is a way to ease implementation of new practices. As data reliability and granularity improves over time and patterns in health worker routes are detected, field missions will be optimized. This means reducing the number of visits necessary to reach equal measurement accuracy, and liberating resources for increasing treatment operations in high-risk areas.

Smart city products serve smart humans

A lot can go wrong when products built in Silicon Valley’s conference rooms hit the roaring streets of emerging countries’ cities: locations that don’t exist, transactions that don’t go through. When technology products mediate human interactions in the physical world, such as a driver picking up a passenger or a health worker conducting door-to-door visits, extreme attention should be paid to reducing operational frictions.

A smart city product is one that integrates in the day-to-day patterns of front line workers, and supports field practices with a high amount of variability and unpredictability. Black-box software solutions that streamline the administrative “assembly line” in a linear fashion don’t work well in contexts like Cali. Field implementers often take into account human factors that make things more functional on the ground — assigning work sectors to prevent women from entering dangerous neighborhoods or accommodate workers who don’t own a motorcycle. Products that are sensitive to human assets can learn from these decision rules so that they can better automate them over time, in a way that is directly actionable.

Tech products need to support agile and flexible physical interactions. Workers have developed street-smart ways to deal with issues they encounter on their daily circuits in the community, such as reporting house inspections with no formal addresses, or facing sudden larvicide shortage. Imposing rigid data entry structures will lead workers to misreport, making data collection more error-prone, while adding to that very operational friction technology is introduced to reduce. Significant usability testing is critical to build street-smart products that adapt to people. Tracking and observing users in their environment helps understand their motivations, and design an experience from which they can derive direct benefits.

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Coordinated and adaptive workflows

Moving data collection to the cloud means public health reports are accessible anywhere, anytime. Providing a single view for all operations enables teams from different departments — Epidemiology, Entomology and Social Work, for example — to work with the same source of truth, and reduces transaction costs of coordination. Instead of making duplicate phone calls to identify households with disease cases, teams can leverage existing data and receive notifications when upstream tasks are completed so they can minimize response time.

In a smart city, adaptive intelligence needs to replace static workflows and more traditional rigid command and control models. Mosquitoes dynamically adapt to human environments. Vector-borne threats are ever-changing, and public health authorities need to respond flexibly to new behaviors. Through technology tools with rich contextual awareness that direct mobile-initiated actions and provide real-time risk-based operational recommendations, city governments can leverage distributed networks of workers and citizens to deliver a faster, better and cheaper response to dynamically adaptive public health threats.

Over six weeks, Devex and our partners will explore what it takes to build a successful smart city, how climate resilient and environmentally friendly infrastructure and technologies are being implemented, and how actors in the global development community are working together toward common goals and engaging local communities in an inclusive way. Join us as we examine what it takes to create our smart cities of the future by tagging #SmartCities and @Devex.

About the authors

Sarah is a program manager at Premise. She leads the deployment of Premise smart vector control technology in Cali, Colombia. Previously, Sarah led business development at a data science nonprofit. She spent five years in Colombia working with the United Nations and managing USAID-funded projects on good governance and economic development. She holds a B.A. in government studies from Sciences Po Paris and a master of international affairs from Columbia University.

David Soloff co-founded Premise in 2012. He has two decades of experience in capital markets, data infrastructure and startups. He serves on the advisory board of Columbia University’s Institute for Data Sciences and is also a venture capitalist with Bowery Capital, an early stage software investment fund. David holds a graduate degree from the University of California, Berkeley, where he was a Javits and Pritchett Fellow pursuing the study of social, economic and linguistic history of the Greek and Roman world. He also holds an undergraduate degree in near eastern languages and cultures from Columbia University.

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